气候变化领域集成服务门户(CCPortal): How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Angstrom exponent

CCPortal

DOI	10.5194/acp-23-1641-2023
	How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Angstrom exponent
	Jin, Jianbing; Henzing, Bas; Segers, Arjo
发表日期	2023
ISSN	1680-7316
EISSN	1680-7324
起始页码	1641
结束页码	1660
卷号	23 期号:2 页码:20
英文摘要	Satellite-based aerosol optical depth (AOD) has gained popularity as a powerful data source for calibrating aerosol models and correcting model errors through data assimilation. However, simulated airborne particle mass concentrations are not directly comparable to satellite-based AODs. For this, an AOD operator needs to be developed that can convert the simulated mass concentrations into model AODs. The AOD operator is most sensitive to the input of the particle size and chemical composition of aerosols. Furthermore, assumptions regarding particle size vary significantly amongst model AOD operators. More importantly, satellite retrieval algorithms rely on different size assumptions. Consequently, the differences between the simulations and observations do not always reflect the actual difference in aerosol amount. In this study, the sensitivity of the AOD operator to aerosol properties has been explored. We conclude that, to avoid inconsistencies between the AOD operator and retrieved properties, a common understanding of the particle size is required. Accordingly, we designed a hybrid assimilation methodology (hybrid AOD assimilation) that includes two sequentially conducted procedures. First, aerosol size in the model operator has been brought closer to the assumption of the satellite retrieval algorithm via assimilation of Angstrom exponents. This ensures that the model AOD operator is more consistent with the AOD retrieval. The second step in the methodology concerns optimization of aerosol mass concentrations through direct assimilation of AOD (standard AOD assimilation). The hybrid assimilation method is tested over the European domain using Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue products. The corrections made to the model aerosol size information are validated through a comparison with the ground-based Aerosol Robotic Network (AERONET) optical product. The increments in surface aerosol mass concentration that occur due to either the standard AOD assimilation analysis or the hybrid AOD assimilation analysis are evaluated against independent ground PM2.5 observations. The standard analysis always results in relatively accurate posterior AOD distributions; however, the corrections are hardly transferred into better aerosol mass concentrations due to the uncertainty in the AOD operator. In contrast, the model AOD and mass concentration states are considerably more accurate when using the hybrid methodology.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000923006400001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273874
作者单位	Netherlands Organization Applied Science Research; Nanjing University of Information Science & Technology
推荐引用方式 GB/T 7714	Jin, Jianbing,Henzing, Bas,Segers, Arjo. How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Angstrom exponent[J],2023,23(2):20.
APA	Jin, Jianbing,Henzing, Bas,&Segers, Arjo.(2023).How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Angstrom exponent.ATMOSPHERIC CHEMISTRY AND PHYSICS,23(2),20.
MLA	Jin, Jianbing,et al."How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Angstrom exponent".ATMOSPHERIC CHEMISTRY AND PHYSICS 23.2(2023):20.